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Both microarray and RNA-seq technologies are powerful tools which are commonly used in differential expression (DE) analysis. Gene expression levels are compared across treatment groups to determine which genes are differentially expressed. With both technologies, filtering and normalization are important steps in data analysis. In this thesis, real datasets are used to compare current analysis methods of two-color microarray and RNA-seq experiments. A variety of filtering, normalization and statistical approaches are evaluated. The results of this study show that although there is still no widely accepted method for the analysis of these types of experiments, the method chosen can largely impact the number of genes that are declared to be differentially expressed.

Estimation of the sensitivity and specificity of cancer screening tests using data from population-level databases is complicated by the lack of independent confirmation of test results using a "gold standard''. The true sensitivity and specificity are unknown and errors in measurement can occur due to subjective clinical judgment, technical imperfections or interpretational differences. A further complication is clustered data (such as patients nested within examiners within screening centre), which are common in population-based screening. We propose a cancer screening model that accommodates the partially unobserved disease status, clustered data structures, general covariate effects, and the dependence between exams. The model is applied to the estimation of the diagnostic accuracy of mammography and clinical breast examination using a cohort consisting of women 50 to 69 years of age screened at the OBSP between January 1, 2002 and December 31, 2003. When offered in addition to mammography, we found CBE may benefit women using hormone therapy but not likely benefit women with dense breast tissues. The thesis also discusses two measures of interest, the length of the pre-clinical state and the false negative rate. Two estimation procedures are proposed to model the pre-clinical state duration, the false negative rate of screening exam, and the underlying incidence rate in the screened population. Both methods assume the sojourn time follows a negative exponential distribution, but we consider two different forms for the false negative rate: 1) constant with time and 2) an exponential function to compensate for the fact that lesions should become easier to detect the closer they are to become clinically evident. The proposed methods are illustrated with another cohort of women who were first screened through the OBSP between January 1, 2003, and December 31, 2004 and were followed up until December 31, 2009. / Thesis / Doctor of Philosophy (PhD)

In this study, I examine how an online cryptocurrency community discusses the issue of climate change. In particular, I examine distinctive themes present within discussions that occur on the r/CryptoCurrency forum hosted by reddit.com. Existing research has demonstrated that there are significant carbon emissions linked to cryptocurrency. However, cryptocurrency primarily exists as a peer-to-peer system, meaning that the individual perceptions of cryptocurrency adopters may provide insight into how to address the emissions problem. Using latent Dirichlet allocation and publicly available textual data from Reddit, I find that Reddit's cryptocurrency community engages in robust discussions pertaining to the energy needed to power cryptocurrency systems, most of which is generated from fossil fuels. Therefore, the discussions identified in this study suggest that the social aspect of cryptocurrency may be important when examining the links between cryptocurrency and climate change since they help identify what subjects related to climate change are important for this community.

The occurrence of pre-existing type 1 and type 2 diabetes in pregnancy has been on the rise, parallel with the current “diabetes pandemic” (Albrecht et al., 2010; Coton et al., 2016; Feig et al., 2014; The Lancet, 2011). Currently, pre-existing diabetes affects up to 2.4% of pregnancies around the world (Deputy et al., 2018; Fadl & Simmons, 2016; Lopez-de-Andres et al., 2020; Tutino et al., 2014; Wahabi et al., 2017). Importantly, women with type 1 and type 2 diabetes are at a high risk of experiencing perinatal complications. Perinatal complications range from neonatal hypoglycemia to fetal and infant death (Feig et al., 2014; Kishida et al., 1989). The risk of complications is related to maternal glycemia; maintaining tight glycemic control within the recommended ranges for pregnancy is associated with a reduced risk of adverse outcomes (Feig et al., 2018; Inkster et al., 2006; Tennant et al., 2014). To achieve this, women experience a heavy burden of diabetes self-management during pregnancy. Little is known regarding the predictors of glycemic control during pregnancies complicated by type 1 and type 2 diabetes and their relationship with self-management factors, such as self-efficacy. Furthermore, the impact of these factors in combination with women’s pregnancy experiences has not been explored. The objective of this thesis was to explore how self-management and support experiences help explain glycemic control among women with pre-existing diabetes in pregnancy. There were four overarching questions: (a) What are the predictors of glycemic control during pregnancy among women with pre-existing diabetes? (b) What is the experience of managing diabetes during pregnancy? (c) What are the diabetes self-management education and support needs during pregnancy among women with pre-existing diabetes? (d) How do the self-management and support experiences of women with pre-existing diabetes in pregnancy help explain their glycemic control? The results of this sandwich thesis aim to answer these questions. The findings showed that women achieved tight glycemic control during pregnancy as they were motivated by the worry of complications for their unborn child. Fear related to complications, feeling unsupported by the healthcare team and a lack of connection with other mothers with diabetes contributed to compromised mental health. Future research should explore the development, implementation and evaluation of interventions to increase mental health support, peer support and support from the healthcare team for this vulnerable population. / Thesis / Doctor of Philosophy (PhD) / Expectant mothers with type 1 and type 2 diabetes have a high risk of complications related to their glucose levels during pregnancy. The relationship between glucose control, mothers’ self-confidence in managing diabetes and their experiences during pregnancy is not well understood. This study explored the factors that affect glucose control and their relationship with the support needs during pregnancy of mothers with type 1 and type 2 diabetes.

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The purpose of this work is to implement four additional inviscid flux methods in the U2NCLE solver being developed at Mississippi State University. The goal is that some or all of these methods may provide benefits over the current options with respect to accuracy or robustness. These four methods include both the Harten, Lax, Van Leer, Einfeldt (HLLE) and Harten, Lax, Van Leer ? Contact (HLLC) methods as well as the Advection Upstream Splitting Method (AUSM) and its successor AUSM+. The HLL family, which includes both HLLE and HLLC are based on the Riemann problem, which is divided into a number of states. The AUSM family attempts to combine the effects of both flux vector and flux difference splittings to create better schemes. Several simple and complex cases were run with each new method and compared to the methods currently available as well as experimental and analytical results when available. The results of the simple tests showed that all the methods were similarly suited for delivering accurate results on simple cases. In more complex cases, however, the AUSM family proved to be less robust and failed to converge for the final case. The HLLE method showed excellent robustness qualities but seemed to over predict the viscous values in several cases. The HLLC method proved equally as accurate and robust as Roe's Method.

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No description available.